Data-Driven Investments at JGSB




Coursework

  • Background courses

    • 665 Python for Business Analytics*
    • 649 Data Mining for Business Analytics
    • 679 Machine Learning for Business Analytics

  • Investments courses

    • 638 Data-Driven Investments Equity*
    • 639 Data-Driven Investments Credit*
    • 767 Data-Driven Investments Lab

Equity course

Inspiration

Data and procedures

  • 100+ monthly features used by GKX
    • financial ratios and growth rates
    • momentum, volatility, beta, market cap, volume
    • analyst forecasts and earnings surprises
  • Industry membership
  • Machine learning (random forests, boosted forests, neural networks) \(\rightarrow\) stock return predictions

Backtests

  • Long best stocks and maybe short worst stocks
  • Analyze portfolio returns
    • Sharpe ratios and drawdowns
    • CAPM alphas and information ratios
    • Fama-French factor attribution analysis
  • Group projects and presentations

Credit course

Inspiration

Objective and data

  • Predict public corporate bankruptcy
  • Data
    • CHS features (profitability, leverage, cash, equity vol, relative market cap, past excess return, MB, and stock price)
    • Expand with add’l 70+ financial analysis ratios from WRDS suite

Methods

Build on CHS to

  • incorporate data science techniques (L1-/L2-penalization, random forest, gradient boosting, neural nets)
  • approach problem from a data science lens (training, validation, testing)
  • produce out-of-sample estimates of default probabilities

Practical applications

  • forecast default
  • forecast ratings changes to identify trading opportunities
  • mispricing based on default probability assessments

Lab course

Data-Driven Investing Lab

  • Full semester (spring)
  • Pre-/co-req is either equity or credit
  • More ML (cross validation, ensemble models, …)
  • New data sources (insider trades, short interest, …)
  • Implement models at Alpaca Brokerage using python API
  • Weekly team reports on performance, model evaluations, and future research

Chicago Quantitative Alliance Competition

  • Several students taking the equity, credit, and lab courses are participating in the CQA investment competition.
    • Aramide Alayi, Amro Elhag, Chris Lopez
    • Daniel Enriquez, Lauren Heckel, Dan McCarthy, Samuel Swanson
  • Run a long/short portfolio with position and cash constraints + no ETFs.
  • Last year, a JGSB MBA team won the competition!
    • 1st in all categories: return, compliance, presentation
    • Arun Kaipuzha, Alice Rothschild, Beau Domingue, Jon Clark, Tyler Freed

This year, at the 2/3 point

Undergraduate Majors

Finance concentration

In addition to the business core curriculum, finance courses include

  • Investments
  • Derivatives
  • Financial statement analysis
  • Advanced corporate finance

Keep an eye out for these students going forward as well!